Overview

Brought to you by YData

Dataset statistics

Number of variables9
Number of observations2000
Missing cells0
Missing cells (%)0.0%
Duplicate rows447
Duplicate rows (%)22.4%
Total size in memory140.8 KiB
Average record size in memory72.1 B

Variable types

Numeric9

Alerts

Dataset has 447 (22.4%) duplicate rowsDuplicates
APL is highly overall correlated with Average Closeness and 5 other fieldsHigh correlation
Assoratativity is highly overall correlated with Betweenness and 1 other fieldsHigh correlation
Average Closeness is highly overall correlated with APL and 5 other fieldsHigh correlation
Average Clustering Coefficient is highly overall correlated with APL and 4 other fieldsHigh correlation
Betweenness is highly overall correlated with AssoratativityHigh correlation
Density is highly overall correlated with APL and 5 other fieldsHigh correlation
Diameter is highly overall correlated with APL and 6 other fieldsHigh correlation
edges is highly overall correlated with APL and 4 other fieldsHigh correlation
nodes is highly overall correlated with APL and 5 other fieldsHigh correlation

Reproduction

Analysis started2024-12-07 21:01:19.958083
Analysis finished2024-12-07 21:01:53.256703
Duration33.3 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

nodes
Real number (ℝ)

High correlation 

Distinct93
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.3335
Minimum10
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:53.491998image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q113
median18
Q330
95-th percentile60.05
Maximum328
Range318
Interquartile range (IQR)17

Descriptive statistics

Standard deviation22.946101
Coefficient of variation (CV)0.90576118
Kurtosis52.217493
Mean25.3335
Median Absolute Deviation (MAD)7
Skewness5.4568638
Sum50667
Variance526.52354
MonotonicityDecreasing
2024-12-07T21:01:53.865119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 240
 
12.0%
12 124
 
6.2%
14 123
 
6.2%
10 119
 
5.9%
13 111
 
5.5%
16 88
 
4.4%
25 81
 
4.0%
17 73
 
3.6%
18 65
 
3.2%
20 65
 
3.2%
Other values (83) 911
45.6%
ValueCountFrequency (%)
10 119
5.9%
11 240
12.0%
12 124
6.2%
13 111
5.5%
14 123
6.2%
15 64
 
3.2%
16 88
 
4.4%
17 73
 
3.6%
18 65
 
3.2%
19 57
 
2.9%
ValueCountFrequency (%)
328 2
0.1%
312 1
 
0.1%
264 1
 
0.1%
154 2
0.1%
152 1
 
0.1%
143 1
 
0.1%
140 1
 
0.1%
139 1
 
0.1%
138 3
0.1%
133 2
0.1%

edges
Real number (ℝ)

High correlation 

Distinct209
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.571
Minimum16
Maximum900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:54.223230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile28
Q140
median59
Q392
95-th percentile209
Maximum900
Range884
Interquartile range (IQR)52

Descriptive statistics

Standard deviation74.395069
Coefficient of variation (CV)0.9120284
Kurtosis22.317605
Mean81.571
Median Absolute Deviation (MAD)24
Skewness3.7650563
Sum163142
Variance5534.6263
MonotonicityNot monotonic
2024-12-07T21:01:54.761161image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 64
 
3.2%
34 60
 
3.0%
89 59
 
2.9%
31 53
 
2.6%
67 52
 
2.6%
46 50
 
2.5%
45 44
 
2.2%
36 39
 
1.9%
37 38
 
1.9%
30 37
 
1.8%
Other values (199) 1504
75.2%
ValueCountFrequency (%)
16 2
 
0.1%
20 15
0.8%
22 3
 
0.1%
23 5
 
0.2%
24 12
0.6%
25 27
1.4%
26 20
1.0%
27 13
0.7%
28 27
1.4%
29 29
1.5%
ValueCountFrequency (%)
900 1
 
0.1%
774 1
 
0.1%
679 2
0.1%
543 1
 
0.1%
530 2
0.1%
527 1
 
0.1%
525 3
0.1%
500 1
 
0.1%
474 1
 
0.1%
459 1
 
0.1%

APL
Real number (ℝ)

High correlation 

Distinct615
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0374969
Minimum1.2
Maximum8.9550048
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:55.162148image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile1.3333333
Q11.5054945
median1.797119
Q32.2469064
95-th percentile3.6116795
Maximum8.9550048
Range7.7550048
Interquartile range (IQR)0.74141193

Descriptive statistics

Standard deviation0.84018458
Coefficient of variation (CV)0.41236115
Kurtosis14.123904
Mean2.0374969
Median Absolute Deviation (MAD)0.34324679
Skewness2.9989587
Sum4074.9939
Variance0.70591013
MonotonicityNot monotonic
2024-12-07T21:01:55.489280image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.393939394 40
 
2.0%
2.166666667 38
 
1.9%
1.436363636 34
 
1.7%
1.4 30
 
1.5%
2.627705628 28
 
1.4%
2.862950058 25
 
1.2%
1.41025641 22
 
1.1%
1.355555556 21
 
1.1%
1.327272727 21
 
1.1%
4.850678733 20
 
1.0%
Other values (605) 1721
86.1%
ValueCountFrequency (%)
1.2 1
 
0.1%
1.222222222 6
0.3%
1.244444444 14
0.7%
1.254545455 3
 
0.1%
1.272727273 4
 
0.2%
1.288888889 9
0.4%
1.290909091 10
0.5%
1.303030303 8
0.4%
1.311111111 8
0.4%
1.318181818 2
 
0.1%
ValueCountFrequency (%)
8.955004848 2
0.1%
8.672314288 1
 
0.1%
8.511752506 1
 
0.1%
7.877854172 2
0.1%
7.164260208 1
 
0.1%
6.989096573 1
 
0.1%
6.198979592 2
0.1%
5.707865169 3
0.1%
5.493253226 1
 
0.1%
5.481920904 1
 
0.1%

Diameter
Real number (ℝ)

High correlation 

Distinct17
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9735
Minimum2
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:55.745312image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median3
Q35
95-th percentile8
Maximum25
Range23
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4332608
Coefficient of variation (CV)0.61237217
Kurtosis15.695612
Mean3.9735
Median Absolute Deviation (MAD)1
Skewness3.0591962
Sum7947
Variance5.9207581
MonotonicityNot monotonic
2024-12-07T21:01:55.951293image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3 569
28.4%
2 530
26.5%
4 366
18.3%
5 185
 
9.2%
6 170
 
8.5%
7 47
 
2.4%
8 41
 
2.1%
12 25
 
1.2%
11 18
 
0.9%
9 17
 
0.9%
Other values (7) 32
 
1.6%
ValueCountFrequency (%)
2 530
26.5%
3 569
28.4%
4 366
18.3%
5 185
 
9.2%
6 170
 
8.5%
7 47
 
2.4%
8 41
 
2.1%
9 17
 
0.9%
10 12
 
0.6%
11 18
 
0.9%
ValueCountFrequency (%)
25 2
 
0.1%
23 4
 
0.2%
18 2
 
0.1%
15 2
 
0.1%
14 5
 
0.2%
13 5
 
0.2%
12 25
1.2%
11 18
0.9%
10 12
0.6%
9 17
0.9%

Assoratativity
Real number (ℝ)

High correlation 

Distinct770
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.23294054
Minimum-0.91257782
Maximum0.58448753
Zeros0
Zeros (%)0.0%
Negative1695
Negative (%)84.8%
Memory size15.8 KiB
2024-12-07T21:01:56.188942image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.91257782
5-th percentile-0.57315104
Q1-0.38623175
median-0.25053822
Q3-0.11734356
95-th percentile0.18123743
Maximum0.58448753
Range1.4970654
Interquartile range (IQR)0.26888818

Descriptive statistics

Standard deviation0.22891095
Coefficient of variation (CV)-0.9827012
Kurtosis0.3728695
Mean-0.23294054
Median Absolute Deviation (MAD)0.13448503
Skewness0.50338159
Sum-465.88108
Variance0.052400222
MonotonicityNot monotonic
2024-12-07T21:01:56.543238image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1607995977 34
 
1.7%
-0.2134632418 32
 
1.6%
0.1846122112 28
 
1.4%
-0.5486415425 26
 
1.3%
-0.02912621359 25
 
1.2%
-0.3440150801 20
 
1.0%
-0.06014347681 20
 
1.0%
-0.5267347751 20
 
1.0%
-0.1926484449 19
 
0.9%
-0.5355375947 18
 
0.9%
Other values (760) 1758
87.9%
ValueCountFrequency (%)
-0.9125778165 3
0.1%
-0.767286155 4
0.2%
-0.7115260903 3
0.1%
-0.7080426412 2
0.1%
-0.7042390811 4
0.2%
-0.7016912754 1
 
0.1%
-0.6969368093 1
 
0.1%
-0.6866267977 4
0.2%
-0.6585554829 2
0.1%
-0.6573821424 2
0.1%
ValueCountFrequency (%)
0.5844875346 3
0.1%
0.5797786379 2
 
0.1%
0.5103965184 5
0.2%
0.5034770515 2
 
0.1%
0.4829253994 2
 
0.1%
0.4342291372 4
0.2%
0.4111776447 2
 
0.1%
0.4035087719 1
 
0.1%
0.3967556607 1
 
0.1%
0.3766081871 2
 
0.1%

Average Clustering Coefficient
Real number (ℝ)

High correlation 

Distinct767
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6366164
Minimum0.06984127
Maximum0.87878788
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:56.837492image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.06984127
5-th percentile0.38070376
Q10.55634921
median0.64586833
Q30.73498951
95-th percentile0.82140917
Maximum0.87878788
Range0.80894661
Interquartile range (IQR)0.1786403

Descriptive statistics

Standard deviation0.1299174
Coefficient of variation (CV)0.20407486
Kurtosis0.5257483
Mean0.6366164
Median Absolute Deviation (MAD)0.089347807
Skewness-0.70911565
Sum1273.2328
Variance0.016878531
MonotonicityNot monotonic
2024-12-07T21:01:57.182380image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5516248196 34
 
1.7%
0.7103174603 32
 
1.6%
0.6627705628 28
 
1.4%
0.531024531 26
 
1.3%
0.2790816327 25
 
1.2%
0.8426406926 20
 
1.0%
0.7477022977 20
 
1.0%
0.5890942391 20
 
1.0%
0.7143578644 19
 
0.9%
0.6149342692 18
 
0.9%
Other values (757) 1758
87.9%
ValueCountFrequency (%)
0.06984126984 2
 
0.1%
0.263350018 1
 
0.1%
0.2655334861 4
 
0.2%
0.2671325052 1
 
0.1%
0.268695441 1
 
0.1%
0.2747047191 1
 
0.1%
0.2758612915 1
 
0.1%
0.2776334776 2
 
0.1%
0.2787110233 11
0.5%
0.2790816327 25
1.2%
ValueCountFrequency (%)
0.8787878788 3
0.1%
0.8766666667 2
 
0.1%
0.8603174603 3
0.1%
0.8587301587 1
 
0.1%
0.8545454545 3
0.1%
0.851031746 2
 
0.1%
0.8509637188 1
 
0.1%
0.8509157509 5
0.2%
0.85 1
 
0.1%
0.8486291486 2
 
0.1%

Average Closeness
Real number (ℝ)

High correlation 

Distinct769
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55812087
Minimum0.11593541
Maximum0.84055944
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:57.509331image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.11593541
5-th percentile0.28712806
Q10.45311053
median0.56737743
Q30.68537088
95-th percentile0.76410776
Maximum0.84055944
Range0.72462404
Interquartile range (IQR)0.23226035

Descriptive statistics

Standard deviation0.14946965
Coefficient of variation (CV)0.26780875
Kurtosis-0.49244422
Mean0.55812087
Median Absolute Deviation (MAD)0.11551349
Skewness-0.42739785
Sum1116.2417
Variance0.022341177
MonotonicityNot monotonic
2024-12-07T21:01:57.828220image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4710592785 34
 
1.7%
0.7259808411 32
 
1.6%
0.3932615665 28
 
1.4%
0.7086313864 26
 
1.3%
0.3586407408 25
 
1.2%
0.2138985476 20
 
1.0%
0.7812897886 20
 
1.0%
0.7270487391 20
 
1.0%
0.735844601 19
 
0.9%
0.3835086322 18
 
0.9%
Other values (759) 1758
87.9%
ValueCountFrequency (%)
0.1159354051 2
0.1%
0.1204600062 1
 
0.1%
0.1224359253 1
 
0.1%
0.1343551539 2
0.1%
0.1462396687 1
 
0.1%
0.1500268795 1
 
0.1%
0.1667121785 2
0.1%
0.1799134641 3
0.1%
0.1855237279 1
 
0.1%
0.1893544945 1
 
0.1%
ValueCountFrequency (%)
0.8405594406 3
0.1%
0.8404545455 1
 
0.1%
0.8369230769 1
 
0.1%
0.8296853147 2
 
0.1%
0.8226923077 3
0.1%
0.8195104895 3
0.1%
0.8177428632 3
0.1%
0.8163286713 5
0.2%
0.8120979021 3
0.1%
0.8071625344 1
 
0.1%

Betweenness
Real number (ℝ)

High correlation 

Distinct676
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04877071
Minimum0.014877931
Maximum0.16483516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:58.109566image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.014877931
5-th percentile0.026554622
Q10.036363636
median0.043449837
Q30.056384409
95-th percentile0.089880952
Maximum0.16483516
Range0.14995723
Interquartile range (IQR)0.020020772

Descriptive statistics

Standard deviation0.019348086
Coefficient of variation (CV)0.39671529
Kurtosis1.8808968
Mean0.04877071
Median Absolute Deviation (MAD)0.0088393563
Skewness1.3181406
Sum97.541421
Variance0.00037434844
MonotonicityNot monotonic
2024-12-07T21:01:58.382162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.03939393939 37
 
1.8%
0.04444444444 37
 
1.8%
0.05072463768 34
 
1.7%
0.08138528139 28
 
1.4%
0.04848484848 28
 
1.4%
0.04657375145 25
 
1.2%
0.0372960373 22
 
1.1%
0.03636363636 21
 
1.1%
0.07701357466 20
 
1.0%
0.03113553114 19
 
0.9%
Other values (666) 1729
86.5%
ValueCountFrequency (%)
0.01487793124 1
 
0.1%
0.0151024112 1
 
0.1%
0.0154210373 2
0.1%
0.01648052162 2
0.1%
0.01656590992 1
 
0.1%
0.01699291332 2
0.1%
0.01729196729 1
 
0.1%
0.01753040719 1
 
0.1%
0.01795215739 3
0.1%
0.01798746017 4
0.2%
ValueCountFrequency (%)
0.1648351648 1
 
0.1%
0.1208791209 1
 
0.1%
0.1179487179 1
 
0.1%
0.1159712344 1
 
0.1%
0.1142191142 3
0.1%
0.1138888889 2
0.1%
0.1131313131 3
0.1%
0.1123188406 2
0.1%
0.1121212121 1
 
0.1%
0.1111111111 1
 
0.1%

Density
Real number (ℝ)

High correlation 

Distinct518
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.37262646
Minimum0.012661296
Maximum0.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-12-07T21:01:58.690861image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.012661296
5-th percentile0.10842845
Q10.22132384
median0.35789474
Q30.51666667
95-th percentile0.66666667
Maximum0.8
Range0.7873387
Interquartile range (IQR)0.29534283

Descriptive statistics

Standard deviation0.17961086
Coefficient of variation (CV)0.48201315
Kurtosis-1.0028615
Mean0.37262646
Median Absolute Deviation (MAD)0.14902874
Skewness0.16146996
Sum745.25293
Variance0.03226006
MonotonicityNot monotonic
2024-12-07T21:01:59.000175image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6060606061 46
 
2.3%
0.5636363636 42
 
2.1%
0.2966666667 34
 
1.7%
0.29004329 30
 
1.5%
0.5454545455 30
 
1.5%
0.6181818182 30
 
1.5%
0.1161440186 25
 
1.2%
0.5897435897 22
 
1.1%
0.4945054945 22
 
1.1%
0.4545454545 21
 
1.1%
Other values (508) 1698
84.9%
ValueCountFrequency (%)
0.01266129634 2
0.1%
0.01855058125 1
0.1%
0.0222951953 1
0.1%
0.03417366947 1
0.1%
0.03773584906 2
0.1%
0.0430138157 1
0.1%
0.04316099984 1
0.1%
0.04498769205 2
0.1%
0.04534440983 1
0.1%
0.04693069307 1
0.1%
ValueCountFrequency (%)
0.8 1
 
0.1%
0.7777777778 6
0.3%
0.7555555556 14
0.7%
0.7454545455 3
 
0.1%
0.7272727273 4
 
0.2%
0.7111111111 9
0.4%
0.7090909091 10
0.5%
0.696969697 8
0.4%
0.6888888889 8
0.4%
0.6818181818 2
 
0.1%

Interactions

2024-12-07T21:01:48.726011image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:20.721101image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:24.746650image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:28.975542image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:34.095308image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:37.844542image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:41.004520image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:43.850955image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:46.407487image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:48.980241image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:21.087274image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:25.323544image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:29.490350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:34.481734image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:38.183146image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:41.479429image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:44.185091image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:46.650835image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:49.296856image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:21.531211image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:25.689620image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:29.821420image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:34.763934image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:38.461346image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:41.807044image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:44.466094image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:46.883872image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:49.753471image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:21.911000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:26.063068image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:30.244295image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:35.189131image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:38.788290image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:42.107882image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:44.773515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:47.175745image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:50.038664image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:22.171184image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:26.341275image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:30.730184image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:35.554770image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:39.074135image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:42.344844image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:45.053391image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:47.427636image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:50.463324image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:22.604230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:26.808154image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:31.130205image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:36.048397image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:39.499591image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:42.716362image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:45.373348image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:47.694209image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:50.760079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:23.032046image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:27.464812image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:31.538821image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:36.511101image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:39.818235image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:43.027069image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:45.660248image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:47.955716image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:52.026119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:23.473554image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:28.091545image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:31.965270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:37.025791image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:40.232588image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:43.289146image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:45.908197image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:48.192145image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:52.337630image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:24.043225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:28.519712image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:32.319638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:37.456924image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:40.671089image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:43.561987image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:46.154363image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-12-07T21:01:48.455840image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-12-07T21:01:59.205362image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
APLAssoratativityAverage ClosenessAverage Clustering CoefficientBetweennessDensityDiameteredgesnodes
APL1.0000.427-0.999-0.5930.315-0.9380.9410.6750.832
Assoratativity0.4271.000-0.429-0.3410.557-0.2130.5100.0130.113
Average Closeness-0.999-0.4291.0000.602-0.3060.941-0.938-0.682-0.837
Average Clustering Coefficient-0.593-0.3410.6021.000-0.1040.640-0.589-0.481-0.577
Betweenness0.3150.557-0.306-0.1041.000-0.0430.386-0.411-0.209
Density-0.938-0.2130.9410.640-0.0431.000-0.844-0.816-0.940
Diameter0.9410.510-0.938-0.5890.386-0.8441.0000.5750.728
edges0.6750.013-0.682-0.481-0.411-0.8160.5751.0000.959
nodes0.8320.113-0.837-0.577-0.209-0.9400.7280.9591.000

Missing values

2024-12-07T21:01:52.728350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-12-07T21:01:53.106955image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

nodesedgesAPLDiameterAssoratativityAverage Clustering CoefficientAverage ClosenessBetweennessDensity
03286798.95500523-0.0777380.3391620.1159350.0244020.012661
13286798.95500523-0.0777380.3391620.1159350.0244020.012661
23129008.67231423-0.1171330.4734540.1204600.0247490.018551
32647748.51175323-0.1195620.4511630.1224360.0286710.022295
41545307.87785425-0.0593320.5966660.1343550.0452490.044988
51545307.87785425-0.0593320.5966660.1343550.0452490.044988
61525434.61084010-0.3633010.5092610.2225320.0240720.047316
71435005.49325312-0.2563020.5422820.1855240.0318670.049247
81404595.05354612-0.1150600.5600480.2033400.0293740.047174
91395273.6500899-0.2846050.5448590.2867960.0193440.054947
nodesedgesAPLDiameterAssoratativityAverage Clustering CoefficientAverage ClosenessBetweennessDensity
199010281.3777782-0.3700310.7237300.7422580.0472220.622222
199110271.4888893-0.1437950.7147620.7022540.0611110.600000
199210201.6888893-0.2571430.7823810.6131760.0861110.444444
199310271.4888893-0.1437950.7147620.7022540.0611110.600000
199410301.3333332-0.3005050.7290480.7640760.0416670.666667
199510301.3333332-0.4192710.7666670.7729610.0416670.666667
199610321.2888892-0.2520140.7782540.7913840.0361110.711111
199710241.5111113-0.1450380.5800000.6719230.0638890.533333
199810311.3111112-0.4548030.8137300.7831370.0388890.688889
199910201.9111113-0.1538460.8766670.5331980.1138890.444444

Duplicate rows

Most frequently occurring

nodesedgesAPLDiameterAssoratativityAverage Clustering CoefficientAverage ClosenessBetweennessDensity# duplicates
30125892.16666750.1608000.5516250.4710590.0507250.29666734
8712401.3939392-0.2134630.7103170.7259810.0393940.60606132
27222672.62770660.1846120.6627710.3932620.0813850.29004328
4811311.4363642-0.5486420.5310250.7086310.0484850.56363626
394421002.8629506-0.0291260.2790820.3586410.0465740.11614425
7011371.3272732-0.5267350.8426410.7812900.0363640.67272720
11613461.4102562-0.3440150.7477020.7270490.0372960.58974420
416521794.85067912-0.0601430.5890940.2138990.0770140.13499220
15214571.3736262-0.1926480.7143580.7358450.0311360.62637419
35332892.6915326-0.5355380.6149340.3835090.0563840.17943518